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Coal mining activities in semi-arid regions can significantly disrupt groundwater systems, leading to a range of ecological and environmental issues, including water quality degradation, soil contamination, and vegetation loss. However, current studies on the evolution of groundwater–soil–vegetation ecosystems in mining areas often overlook or overly simplify the complex nonlinear interactions among these components. This study uses the Bojianghaizi Basin in China as a case study, applying remote sensing inversion, hydrogeological surveys, and soil habitat quality assessments, alongside the PCA-APCS-MLR, EWM, and OLS models, as well as hydrogeochemical methods, to conduct a comparative analysis of groundwater-soil-vegetation system evolution under the influence of coal mining activities and natural conditions. The results show that groundwater chemical types in areas affected by coal mining are primarily Cl·SO4-Na, whereas those under natural conditions are predominantly HCO3-Ca. Groundwater in the study area is influenced by the dissolution of carbonate and sulfate rocks and cation exchange adsorption. However, compared to natural conditions, groundwater in mining areas is more strongly impacted by the dissolution of calcium-magnesium-bearing minerals, such as feldspar and pyroxene. Analysis using the PCA-APCS-MLR model attributes the factors influencing groundwater chemical characteristics in the study area to four main sources: evaporation concentration, water-rock interactions and ion exchange, agricultural pollution, acid production from the oxidation of sulfur-bearing ores, and other sources. Significant spatial differences exist in the coupling relationships between groundwater chemical characteristics (x1), soil characteristics (x2), and fraction vegetation coverage (FVC, y) on the north and south sides of the study area's lakes. The multiple regression models for the three variables in the mining-disturbed and naturally regulated areas, constructed using the EWM and OLS methods, are: yNorth=−210.246x1−37.228x2+124.727 (R2=0.607), ySouth=−142.642x1−60.186x2+105.574 (R2=0.784). The model results indicate that changes in groundwater chemical characteristics are the primary factors affecting FVC. Compared to the mining-disturbed area, changes in soil characteristics have a more significant impact on FVC in the naturally regulated area. This study can not only provide a scientific basis for the sustainable development of similar mining areas globally but also provide guidance for ecological management and the rational utilization of water and soil resources in semi-arid coal mining areas.

半干旱地区的煤矿开采活动会显著干扰地下水系统，引发一系列生态与环境问题，包括水质退化、土壤污染以及植被丧失。然而，当前针对矿区地下水-土壤-植被生态系统演化的研究，往往忽视或过度简化了各组分间复杂的非线性相互作用。本研究以中国泊江海子盆地为研究案例，结合遥感反演、水文地质调查、土壤生境质量评价，以及主成分分析-绝对主成分分数-多元线性回归模型（PCA-APCS-MLR）、熵权法（Entropy Weight Method, EWM）和普通最小二乘法（Ordinary Least Squares, OLS）与水文地球化学方法，对比分析了煤炭开采活动与自然条件影响下的地下水-土壤-植被系统演化过程。研究结果表明：受煤炭开采影响区域的地下水化学类型以Cl·SO4-Na为主，而自然条件下的地下水化学类型则以HCO3-Ca为主。研究区地下水受碳酸盐岩、硫酸盐岩溶解作用及阳离子交换吸附作用影响，但相较于自然条件，矿区地下水受长石、辉石等含钙镁矿物溶解的影响更为显著。通过PCA-APCS-MLR模型分析，研究区地下水化学特征的影响因素可归结为四大主要来源：蒸发浓缩作用、水-岩相互作用与离子交换、农业污染、含硫矿石氧化产酸作用及其他来源。研究区湖泊南北两侧的地下水化学特征（x1）、土壤特征（x2）与植被覆盖度（Fraction Vegetation Coverage, FVC, y）之间的耦合关系存在显著空间差异。本研究采用EWM与OLS方法构建了采矿扰动区与自然调控区三个变量的多元回归模型，分别为：y北=-210.246x1-37.228x2+124.727（R²=0.607），y南=-142.642x1-60.186x2+105.574（R²=0.784）。模型结果显示，地下水化学特征变化是影响FVC的核心因素。相较于采矿扰动区，自然调控区的土壤特征变化对FVC的影响更为显著。本研究可为全球同类矿区的可持续发展提供科学依据，同时为半干旱煤矿区的生态治理与水土资源合理利用提供指导。